Meta analysis plays a key role in setting policy and in planning new research. In the field of substance abuse prevention, meta analyses have been used to determine the relative impact of competing treatments for addiction, to estimate prevalence of addiction-related diseases, to plan targeted interventions, to assess the cost-effectiveness of competing treatments, and to assist in planning more effective research. A key element in any meta analysis is the forest plot which serves as the visual representation of the data. The forest plot shows at a glance if the overall effect reported in the analysis is based on many studies or a few; on studies that are precise or imprecise; whether the treatment effects for all studies tend to line up in a row, or whether they vary substantially from one study to the next. The plot puts a face on the statistics, helping to ensure that they will be interpreted properly, and highlighting anomalies such as outliers that require attention. The forest plot is at once concise and compelling, the appellation itself reflecting the goal of the meta analysis, to see "the forest for the trees". The goal of this application is to develop software for creating forest plots. The program will function both as a stand-alone program and also as module within a program that runs analyses. It will allow the user to import data from other programs, create a forest plot and customize the plot extensively, and then export the plot to other programs. [unreadable] [unreadable]